Smartphones of today typically comprise a fast central processing unit (CPU), a large display and a fast access to a network such as Internet, and therefore often consume considerable amounts of energy.
Battery consumption can be reduced by focusing on user device-related network behavior optimization. This can only be achieved with some compromise on quality of experience e.g., the user has to switch to a lower performance channel or periodically switch off the radio unit to spare energy.
Moreover, optimization for the battery has paramount importance if the battery is close to getting depleted. For this reason it would be useful to have access to charging information of the UE and to take into account a battery status at optimization decisions.
From Zhang, et al., “Accurate online power estimation and automatic battery behavior based model generation for smartphones” in 2010 IEEE/ACM/IFIP International conference on Hardware/Software Co-design and System Synthesis, an automated power model construction technique using built-in battery voltage sensors and knowledge of battery discharge behavior to monitor power consumption, is known. This technique does not require external measurement equipment. A second component of this method applies the constructed power models for online power estimation. This method is totally terminal based, as it collects data locally, creates power models locally and utilizes them locally.
There is a need for information about charging of a user device without the need to install software components on the user devices.